1. Technical Field of the Invention
The present invention generally relates to a control unit and a control method of appropriately maintaining an output signal of a nonlinear system by carrying out adaptive control of variable impedance components, and especially relates to a control unit and a control method of appropriately maintaining a signal received by an adaptive antenna system that has two or more antenna elements.
2. Description of the Related Art
In the technical field, appropriately maintaining an output signal is often carried out by optimizing impedance by an optimization technique that uses a perturbation method in a nonlinear system wherein an output signal changes depending on the impedance of two or more components.
FIG. 1 is a conceptual diagram showing an example of a conventional control system 100. The control system 100 serves a radio frequency (RF) processing type adaptive antenna system, and is a nonlinear system wherein the impedances of two or more RF components (L, C) are unknown, and two or more received signals are added and output. The control system 100 includes two or more antenna elements 102, the quantity of which is expressed as M+1, and an adder 104 that combines signals from the antenna elements 102. The output of the adder 104 is provided to an analog-to-digital converter 106. The output of the analog-to-digital converter 106 is provided to a control unit 108.
Out of the M+1 antenna elements, each of M antenna elements includes a phase shift circuit 110 that consists of an inductor Li connected in series and a capacitor Ci (i=1, . . . , M) connected in parallel to the antenna element 102. The inductance of the inductor Li and the capacitance of the capacitor Ci are adjusted by a control signal provided by the control unit 108. Contents xi (i=1, . . . , 2M) of the control signal specify a signal for setting up the impedance of the inductor Li and the capacitor Ci.
FIG. 2 is a flowchart showing a control flow 200 of the control system 100 mainly performed by the control unit 108, the control flow 200 employing the perturbation method. The control flow 200 starts at Step 202. At Step 204, impedance xi of two or more components (inductors Li and capacitors Ci) is set at a suitable initial value. At Step 206, a parameter m relevant to the number of repetition times of the process is set at an initial value 0.
At Step 208, an evaluation function value f(x) is obtained, where f(x) varies depending on a signal y(x), where x=x1, x2, . . . , x2M, output by the analog-to-digital converter 106 (FIG. 1). The evaluation function value is stored as a fiducial point f0(x).
At Step 210, the parameter m is incremented by one.
At Step 212, the value of the impedance xm of the m-th component is changed to xm+Δxm. For example, if the value of m is 1, a minute change is added to the value of the inductor Ll. The minute change causes the output signal y(x) to change.
At Step 214, the evaluation function value f(x) is calculated based on the output signal y(x).
At Step 216, a slope (gradient) vector ∇f is calculated by computing the difference between the evaluation function values f(x) before and after the minute change of the impedance xm. The gradient vector ∇f is a vector quantity that has 2M components, and each component is calculated by the following formula.(∇f)xm=f(x1, . . . , xm+Δxm, . . . , x2M)−f0(x1, . . . , xm, . . . , x2M)
At Step 218, the added minute change Δxm is deducted, and the value of xm returns to the original value.
At Step 220, it is determined whether the parameter m is equal to or less than 2M. If the determination is affirmative, the process returns to Step 208, and other components of the gradient vector ∇f are calculated. Otherwise, if m is determined to be greater than 2M, all the components of the gradient vector ∇f have been calculated.
At Step 222, the impedance value xi is updated using the calculated gradient vector ∇f. The gradient vector ∇f represents the direction in which a slope (inclination) changes most rapidly in the coordinate (x1, x2, . . . , x2M) of the curved surface expressed by f. That is, the maximum or the minimum value (the desired optimal value) of the evaluation function value f is present in the direction indicated by ∇f. Accordingly, the impedance value x is updated to x+α∇f, where α represents a step size in the direction of ∇f.
At Step 224, it is determined whether the impedance value is satisfactorily converged by comparing the impedance value with the previous impedance value. If negative, the process returns to Step 206 for further updating. If affirmative, the process proceeds to Step 226, and the control flow 200 is ended.
The optimization technique wherein the gradient vector ∇f is calculated, and the impedance value is updated by adding a minute change to the impedance using the perturbation method has been disclosed by, e.g., JPA 2002-118414, Robert J Dinger, “A Planar Version of a 4.0 GHz Reactively Steered Adaptive Array”, IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. AP-34, No.3, March 1986, and Robert J Dinger, “Reactively Steered Adaptive Array Using Microstrip Patch Components at 4.0 GHz”, IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. AP-32, No.8, August 1984.
It is common for the above control technique to use a semiconductor integrated circuit to form the variable impedance component such as a variable inductor and a variable capacitor. However, while the common practice is advantageous in that a high response speed is available when changing the impedance, a disadvantage is that high power is consumed. This is particularly disadvantageous for a small appliance that uses a battery.
On the other hand, an impedance variable component is available, wherein the impedance is mechanically changed using a micro electro mechanical system (MEMS). The impedance can be changed by various methods, and examples are to change the impedance by changing the interval between two plates of a capacitor, and by changing the amount of insertion of a magnetic core of an inductor. Indeed, the MEMS type component consumes very little power, compared with the semiconductor integrated circuit, and it is possible to solve the problem concerning power consumption. However, the response time of the MEMS component tends to be longer than the semiconductor integrated circuit for the same impedance. Especially, when a process such as the control flow 200 is used in order to obtain a gradient vector ∇f, the slow response poses a problem in that the gradient vector ∇f cannot be promptly calculated. That is, an MEMS type component is not capable of accurately following changes in a nonlinear system.